TY  - JOUR
A1  - Hasan, Firman Noor
N2  - The corrupt behavior of government officials is a problem that worries the public and threatens the integrity of the government system. In today's digital era, social media is an important means for the public to voice their opinions and sentiments on social issues, including the corruption of government officials. This study aims to analyze public sentiment toward the corrupt behavior of government officials based on tweet data on social media using the Naïve Bayes Classifier method. Tweet data is taken from social media Twitter related to corruption cases involving government officials within a certain period. The data is then processed to remove irrelevant elements and extract the sentiments contained in the tweets The Naïve Bayes Classifier method is applied to classify these tweets of positive, negative, or neutral sentiment toward corrupt behavior from government officials. The results of this study conclude that the public is very angry, disappointed, and has a low level of trust in corrupt behavior committed by government officials. Proven by the most dominant sentiment category is negative sentiment with 224 data and 95 data fall into the positive sentiment category.
IS  - 4
TI  - (MIB - S3) - Syakir, Hasan [2023-10-24]
EP  - 1805
AV  - public
ID  - repository29814
UR  - https://ejurnal.stmik-budidarma.ac.id/index.php/mib/article/view/6648
PB  - STMIK Budi Darma
VL  - 7
Y1  - 2023/10/24/
JF  - MIB: Media Informatika Budidarma
SN  - 2548-8368
SP  - 1796
ER  -